Determining Colors of Objects in Digital Images

5. The method of claim 1, further comprising identifying the object in the digital image utilizing an object detection neural network.

7. The non-transitory computer-readable medium of claim 6, further comprising instructions that, when executed by the at least one processor, the at least one processor to perform operations comprising: generating a second color similarity region corresponding to a second color by grouping one or more additional alternative versions of the second color and the second color together within the multidimensional color space.

9. The non-transitory computer-readable medium of claim 8, wherein the one or more color attributes of the first color modified within the second color model comprise a color brightness, a color hue, or a color saturation level.

10. The non-transitory computer-readable medium of claim 8, wherein modifying the one or more color attributes of the first color within the second color model comprises reducing a brightness level of a first color copy in the second color model.

11. The non-transitory computer-readable medium of claim 6, wherein the first color similarity region for the first color comprises a first color point for the first color and a plurality of mapped alternative color points for the first color mapped to the multidimensional color space.

12. The non-transitory computer-readable medium of claim 11, wherein generating the set of color-matching scores for the object based on the set of color correspondences between the plurality of pixels and the set of color similarity regions comprises generating a first color-matching score for the object based on determining distances in the multidimensional color space between each of the pixels of the plurality of pixels of the object and each of the plurality of mapped alternative color points and the first color point.

15. The system of claim 14, wherein the at least one processor is further configured to receive a request to select pixels of an instance of the object in the digital image having the first color.

16. The system of claim 15, wherein the at least one processor is further configured to cause the system to: identify the plurality of instances of the object in the digital image in response to the request, wherein identifying the plurality of instances of the object comprises utilizing an object detection neural network to generate an approximate boundary for each instance of the object.

17. The system of claim 16, wherein the at least one processor is further configured to cause the system to: determine the pixels associated with each instance of the object by generating an object mask for each instance of the object from the approximate boundary for each instance of the object utilizing an object mask neural network.

18. The system of claim 14, wherein the first color similarity region comprises a complex-shaped color similarity region comprising a union of multidimensional spheres.

19. The system of claim 16, wherein the at least one processor is further configured to cause the system to generate the color-matching score for each instance of the object by determining a percentage of pixels of each instance of the object located within the first color similarity region.

20. The system of claim 19, wherein determining a percentage of pixels of each instance of the object located within the first color similarity region comprises determining a percentage of a subset of pixels of each instance of the object located within the first color similarity region.